Name
Title | ||
|---|---|---|
Automatic generation of land use maps using aerial orthoimages and building floor data with a Conv-Depth Block (CDB) ResU-Net architecture |
Abstract | ||
|---|---|---|
•CDB ResU-Net was developed to automate the process of LU map generation.•The proposed neural network has higher accuracy than the existing neural networks.•Addition of building floor data improved the accuracy in residential areas.•Combining ancillary data helps to improve the overall accuracy of classification. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.jag.2022.102678 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | DocType | Volume |
Aerial orthoimages,Land use map,Digital topographic map,Building floor data,ResU-Net | Journal | 107 |
ISSN | Citations | PageRank |
1569-8432 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Suhong Yoo | 1 | 0 | 0.34 |
| Ji-Sang Lee | 2 | 0 | 0.34 |
| Mohammad Gholami Farkoushi | 3 | 0 | 0.34 |
| Eunkwan Lee | 4 | 0 | 0.34 |
| Hong-Gyoo Sohn | 5 | 0 | 0.68 |